[imgcontainer][img:Pop+with+no+BB+Access%2C+2010.jpg] [source]Source: National Broadband Map Data aggregated to County Level, 2010[/source] Figure 1. Percentage of Population with No Wired Broadband Availability, by Metropolitan Status (2010). The size of the red dots indicates the percentage of a county’s population that lacks wired broadband. The larger the dot, the greater the percentage of the population that lacks service. Enlarge the map. [/imgcontainer]
EDITOR’S NOTE: Today we begin a series of weekly articles on rural broadband written by three researchers noted for their work in rural development, economics and communications policy. Support for this research was provided by the National Agricultural and Rural Development Policy Center (NARDeP).
Regular readers of the Yonder are used to seeing stories about the importance of broadband access for rural residents. They are also familiar with stories about difficulties in obtaining a reliable broadband connection in rural areas. However, for a long time, there was very little data on exactly where broadband was and was not available across the country.
The National Broadband Map came along in 2010 and provided the first, low-level look at exactly what parts of the country had access to broadband connections. The map provided broadband-related information for each Census Block (of which there are around 8 million in the United States), including the number of providers, advertised download / upload speeds, and technology utilized. You can check out the map here and see what it has to say about where you reside.
The initial 2010 dataset contained a unique variable – the percentage of the population in each Census Block for which no “wired” broadband infrastructure was available. The definition used for broadband (3 mbps download, 768 kbps upload) is slightly lower than the current Federal Communications Commission (FCC) definition (4 mbps down, 1 mbps up), but is still a useful measure for determining gaps in availability. The official report from the FCC (see Table 2 on page 29) associated with this initial version of the map suggested a striking gap between rural and urban availability: 23.7% of rural residents lacked this type of access, compared with only 1.8% of non-rural (i.e. urban) residents. (It is worth noting that the picture of broadband availability painted by only the “wired” infrastructure is much different than when “wireless” is also considered – a fact that has been pointed out by other Yonder articles).
When the Census Block data is aggregated to the county level (which allows for breakouts of different levels of rurality) and mapped, it becomes apparent that broadband availability varies greatly across the country. (See the map at the top of this article.)
Clearly, some states have large portions of their populations that still lack access to wired broadband infrastructure. West Virginia, South Dakota, and Oklahoma look particularly poor. Not surprisingly, most of the metropolitan counties in the map have the smallest dots — meaning that most of their population does have access to relatively high levels of broadband infrastructure. Similar trends have been noted for broadband speeds.
We can also look at general levels of broadband availability across the three types of counties: metro (which typically have a city of 50,000 or more), micro (which typically have a city of 10,000 or more), and non-core (no cities of 10,000 or more). The figure to the right
[imgcontainer right] [img:chart.jpg] [source]Source: National Broadband Map Data aggregated to County Level, 2010. [/source] Figure 2. Proportion of Counties Meeting No Broadband Availability Thresholds (by metropolitan status), 2010. The graph shows that the availability of broadband decreases for counties as they move from metropolitan (generally, counties with cities of 50,000 residents and up), micropolitan (counties with cities of 10,000 to fewer than 50,000) and noncore (counties that have no cities of more than 10,000 residents). [/imgcontainer]
demonstrates that the more rural areas are significantly worse off in terms of the availability of wired broadband infrastructure. In fact, nearly 30% of all noncore counties have more than 40% of their population lacking access to wired broadband infrastructure. Alternatively, we can look at where broadband availability is best — where less than 2% of the county population lacks access. Only 5% of non-core counties meet this highest category of availability, compared to nearly 40% of metro counties.
The table at the bottom of this article documents these broadband availability gaps (metro – micro and metro – noncore) for each state. In some states, the availability gap is not all that great; in others it is significant. Some large metro – noncore gaps are found in larger, relatively rural states where it might be expected (South Dakota, Idaho, Montana, Alaska), but others are found in smaller states (Maryland and Louisiana). There are only a handful states where the metro – noncore availability gap is in the single digits (South Carolina, Pennsylvania, Massachusetts, and Maine).
Of course, availability of broadband infrastructure is only the first piece of the puzzle. Adoption rates and how the technology is used greatly affect the potential for economic and societal gains.
The authors of this article have put together a comprehensive look at the broadband situation in rural America, including availability and adoption trends over time, impacts to the rural economy, and policy prescriptions. Over the next several weeks, they will break down their most important findings and attempt to move the rural broadband conversation forward.
Brian Whitacre is an associate professor in the department of Agricultural Economics at Oklahoma State University. His research, extension, and teaching appointments are focused on rural economic development, with a heavy emphasis on the role of broadband access.
Roberto Gallardo is an associate Extension professor at Mississippi State University, where he serves as project manager for the statewide broadband adoption initiative.
Sharon Strover is a Regents Professor in Communication at the University of Texas, where she directs the Telecommunications and Information Policy Institute. Her teaching and research focus on technology, policy and regulation.
Funding for this study was provided by the National Agricultural and Rural Development Policy Center (NARDeP).
Table 1. Percentage of Population with no Wired Broadband Access Availability, by County Typology, 2010
|
|
Metro |
Micro |
Noncore |
|
Metro – Micro Gap |
Metro – Noncore Gap |
|
Alabama |
7.4% |
14.2% |
30.1% |
6.7% |
22.7% | |
|
Alaska |
5.7% |
10.0% |
61.7% |
4.3% |
56.1% | |
|
Arizona |
2.2% |
12.3% |
63.2% |
10.1% |
61.0% | |
|
Arkansas |
5.8% |
24.1% |
27.3% |
18.3% |
21.5% | |
|
California |
2.8% |
28.1% |
23.3% |
25.3% |
20.5% | |
|
Colorado |
2.0% |
14.1% |
23.7% |
12.2% |
21.7% | |
|
Connecticut |
0.7% |
0.7% |
– |
0.0% |
– | |
|
Delaware |
2.2% |
6.6% |
– |
4.3% |
– | |
|
Florida |
2.5% |
7.2% |
20.9% |
4.7% |
18.4% | |
|
Georgia |
1.5% |
8.6% |
15.1% |
7.1% |
13.5% | |
|
Hawaii |
0.0% |
5.0% |
– |
4.9% |
– | |
|
Idaho |
5.8% |
20.2% |
40.1% |
14.4% |
34.3% | |
|
Illinois |
1.1% |
14.2% |
24.0% |
13.0% |
22.9% | |
|
Indiana |
2.8% |
7.5% |
17.1% |
4.7% |
14.3% | |
|
Iowa |
3.2% |
7.3% |
15.1% |
4.1% |
11.9% | |
|
Kansas |
4.7% |
8.1% |
20.4% |
3.4% |
15.7% | |
|
Kentucky |
4.5% |
10.9% |
25.3% |
6.4% |
20.8% | |
|
Louisiana |
4.5% |
16.8% |
36.5% |
12.3% |
32.0% | |
|
Maine |
2.5% |
2.3% |
10.1% |
-0.2% |
7.5% | |
|
Maryland |
2.6% |
6.8% |
36.2% |
4.2% |
33.6% | |
|
Massachusetts |
0.9% |
– |
7.1% |
– |
6.1% | |
|
Michigan |
3.4% |
12.3% |
27.1% |
8.9% |
23.7% | |
|
Minnesota |
4.0% |
12.5% |
26.6% |
8.5% |
22.6% | |
|
Mississippi |
4.7% |
12.5% |
26.9% |
7.8% |
22.2% | |
|
Missouri |
2.2% |
16.2% |
27.9% |
14.0% |
25.7% | |
|
Montana |
14.0% |
15.6% |
50.8% |
1.5% |
36.8% | |
|
Nebraska |
2.2% |
15.7% |
28.3% |
13.5% |
26.2% | |
|
Nevada |
0.9% |
11.8% |
21.0% |
10.9% |
20.1% | |
|
New Hampshire |
3.6% |
13.9% |
14.0% |
10.3% |
10.4% | |
|
New Jersey |
0.7% |
– |
– |
– |
– | |
|
New Mexico |
9.3% |
24.5% |
25.6% |
15.2% |
16.2% | |
|
New York |
0.5% |
9.9% |
10.7% |
9.4% |
10.2% | |
|
North Carolina |
4.2% |
10.5% |
17.0% |
6.3% |
12.8% | |
|
North Dakota |
3.1% |
23.7% |
31.5% |
20.7% |
28.4% | |
|
Ohio |
1.4% |
8.9% |
22.1% |
7.5% |
20.7% | |
|
Oklahoma |
8.6% |
21.0% |
42.1% |
12.4% |
33.5% | |
|
Oregon |
1.1% |
10.6% |
17.5% |
9.5% |
16.5% | |
|
Pennsylvania |
1.0% |
5.3% |
6.7% |
4.3% |
5.7% | |
|
Rhode Island |
0.2% |
– |
– |
– |
– | |
|
South Carolina |
10.5% |
16.8% |
14.7% |
6.2% |
4.1% | |
|
South Dakota |
11.4% |
10.5% |
49.1% |
-0.9% |
37.7% | |
|
Tennessee |
3.7% |
10.7% |
22.1% |
7.0% |
18.4% | |
|
Texas |
3.8% |
16.5% |
28.2% |
12.7% |
24.4% | |
|
Utah |
0.6% |
5.3% |
17.4% |
4.7% |
16.8% | |
|
Vermont |
3.5% |
11.3% |
13.9% |
7.7% |
10.4% | |
|
Virginia |
8.0% |
20.9% |
31.8% |
12.9% |
23.9% | |
|
Washington |
1.7% |
11.0% |
22.8% |
9.4% |
21.1% | |
|
West Virginia |
37.0% |
54.3% |
60.1% |
17.3% |
23.2% | |
|
Wisconsin |
2.9% |
12.0% |
23.9% |
9.1% |
21.1% | |
|
Wyoming |
2.5% |
14.3% |
23.8% |
|
11.8% |
21.3% |
|
“-” indicates that there are no counties of this typology in that state |
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